{"id":"W2601262767","doi":"10.4236/ajps.2017.84051","title":"Identification of Quantitative Trait Loci Controlling Floral Morphology of Rice Using a Backcross Population between Common Cultivated Rice, <i>Oryza sativa</i> and Asian Wild Rice, <i>O. rufipogon</i>","year":2017,"lang":"en","type":"article","venue":"American Journal of Plant Sciences","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Biology; Oryza sativa; Quantitative trait locus; Oryza rufipogon; Backcrossing; Lemma (botany); Botany; Glume; Stamen; Population; Poaceae; Genetics; Gene; Pollen","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002285335,0.0004310567,0.0002803379,0.0004567441,0.0001903525,0.00018523,0.0002944028,0.0001895476,0.0008534839],"category_scores_gemma":[0.0001529411,0.0002451702,0.0005509775,0.0003402806,0.0002262033,0.00008902811,0.0003296394,0.0004167608,0.000205271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003139138,"about_ca_system_score_gemma":0.0002199664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002097033,"about_ca_topic_score_gemma":0.003852061,"domain_scores_codex":[0.9998579,0.00001163781,0.00001701236,0.00006417331,0.0000262323,0.00002296583],"domain_scores_gemma":[0.9997655,0.00005419103,0.00006586684,0.00002656002,0.00002099787,0.00006690071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001104016,0.00003648405,0.001618073,0.00001173283,0.00001385036,0.00006201276,0.00007030727,0.00003535454,0.9969293,0.00002721419,0.0000062874,0.001078892],"study_design_scores_gemma":[0.0001846583,0.001222217,0.6081788,0.00001950621,0.0004392873,0.001618175,0.0003880896,0.003435053,0.3817996,0.0001059932,0.002551811,0.00005682976],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982181,0.00003987896,0.001255647,0.000007642243,0.000003647984,0.00001916109,0.0002266403,0.00002309148,0.0002061593],"genre_scores_gemma":[0.990522,0.0001178077,0.005637212,0.0000332475,0.000005214427,0.00009042936,0.001575914,0.00005780043,0.001960384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002097033,"threshold_uncertainty_score":0.004169583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05687576594666746,"score_gpt":0.3212881985499135,"score_spread":0.264412432603246,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}